Xiaoxuan Zhang.
An engineer by training, a quant by aspiration — I build high-performance trading systems powered by parallel computing, with a long-term vision of becoming an independent quantitative trader in the crypto space.
Hi, I am,
Experience
Led the full lifecycle development of Lava, a proof-of-capacity (PoC) based cryptocurrency forked from Bitcoin Core.
Architected and implemented consensus modifications to support PoC mining, enhancing energy efficiency compared to PoW.
Oversaw system integration, wallet and miner tools, and network bootstrapping.
Managed codebase releases, testnet deployment, mainnet launch, and listing on HitBTC exchange.
Coordinated a small remote team of developers, ensuring agile delivery and robust documentation.
Began trading in the China A-share market in 2013, later expanded into cryptocurrency markets in 2018.
Developed and published open-source Pine Script strategies on TradingView, focusing on momentum, volatility, and pattern-based signals.
Built a custom GPU-accelerated C++ quantitative trading platform, capable of high-speed multi-asset backtesting and real-time strategy execution using CUDA.
Continuously iterating on architecture and strategies, with strong emphasis on parallel computing, infrastructure scalability, and low-latency data pipelines.
Led the High-Availability (HA) system design and development of Mavenir’s distributed element control platform, ensuring robust uptime and fault tolerance.
Focused on telecom-grade reliability, implementing failover, state recovery, and multi-node synchronization.
Projects
C++
CUDA
GeekChomolungma
A quantitative platform based on C++ and CUDA. It is built up to do quantitative trading in specific cryptocurrency exchanges. Still working on it.
C++
Bitcoin
Lava
A proof-of-capacity (PoC) based cryptocurrency forked from Bitcoin Core.
Option Pricing
volatility
Smile
Option Pricing
A clean and simple Hugo template for personal portfolio and blog.
Education
2024 - 2026
Master of Computational Science
University of Amsterdam
GPA:
8.0 out of 10.0
- Built a solid foundation in stochastic differential equations (SDEs), Monte Carlo simulations, and numerical methods for option pricing.
- Gained in-depth understanding of numerical PDE solvers, discretization techniques, and iterative schemes in the context of scientific computation.
- Completed advanced coursework in parallel systems, GPU computing (CUDA), and Big Data infrastructure.
2013 - 2015
Master of Control Engineering
Wuhan University
GPA:
3.5 out of 4.0
- Core courses included Matrix Theory, Control Theory, Numerical Analysis, and Optimization.
- Proficient in modeling and simulation of industry processing, focusing on industry efficiency solutions by regression and classification tools like SVM, LS-SVM, and PSO.